Can we really start without buying sensors?

For most plants, yes — to a point. Your CMMS failure history, SCADA alarms and MES quality events already hold recurring patterns. Connecting them gives an early win and shows which assets later justify sensors. Some failure modes still need condition sensors; you’ll know which after the baseline.

Is this the same as condition-based maintenance?

Effectively yes — predictive maintenance acts on the equipment’s actual condition and data, rather than a fixed calendar. This guide is about starting that data-driven approach from the data you already have.

How is 90 days realistic with no model training?

The first value comes from making existing signal queryable and traceable, not from training a model on labelled data. You connect a source, baseline it, surface patterns, and act — measured against day one.

What do we actually need to connect first?

One critical line or asset family: its CMMS history and the relevant SCADA alarms, read-only. Add ERP/MES context where root cause requires it.

RESOURCES · GUIDE

Predictive maintenance in 90 days, with the data you already have.

Most predictive-maintenance projects stall on a sensor rollout that takes a year to fund and install. But a lot of the signal is already in your CMMS, SCADA and MES. Here is a 90-day plan that starts from existing data — and tells you honestly when sensors are actually worth it.

THE RESET Predictive doesn’t have to start with sensors.

The default story says predictive maintenance = install vibration and temperature sensors, stream them to a platform, wait for a model to learn. That is one path, and a slow one. The faster first step: the failure history in your CMMS, the alarms and tags in your SCADA, and the quality events in your MES already contain patterns — recurring faults, codes that precede stoppages, lots tied to drifts. Connect that first; add sensors where the data you have proves they’d pay off.

THE PLAN Ninety days, three phases.

01Days 1–30 — Connect & baselinePick one critical line or asset family. Connect the CMMS (failure history, work orders) and the SCADA alarms, read-only. Establish the baseline: what fails, how often, what it costs in downtime, and which faults recur.
02Days 31–60 — Find the patternsSurface the signals already present: error codes that precede a stoppage, interventions that cluster, lots or batches tied to a parameter drift across the MES. Make each finding queryable and traceable to the record it came from.
03Days 61–90 — Act & proveTurn the strongest patterns into early-warning checks and the right procedure at the right moment. Measure the delta on MTTR and downtime against the day-1 baseline — and list the few assets where physical sensors would now clearly pay back.

WHAT TO MEASURE Prove it on numbers you already track.

MTTRmean time to repair — the search-and-diagnose part is where connected data cuts the most.
Unplanned downtimehours lost to faults that recur — the patterns you surface should reduce repeats.
First-time-fix ratedid the technician arrive with the right doc, history and procedure?
OEE / TRS trendthe availability component moves first when diagnosis speeds up.

BE HONEST When sensors really are the answer.

Existing data can’t see what was never recorded. For failure modes with no early footprint in your systems — bearing wear, cavitation, insulation breakdown — condition sensors are the right tool. The point isn’t “never instrument”; it’s “instrument the assets your own data has shown deserve it,” after the connect-first step, not before.

FAQ What teams ask before starting.

Can we really start without buying sensors?: For most plants, yes — to a point. Your CMMS failure history, SCADA alarms and MES quality events already hold recurring patterns. Connecting them gives an early win and shows which assets later justify sensors. Some failure modes still need condition sensors; you’ll know which after the baseline.
Is this the same as condition-based maintenance?: Effectively yes — predictive maintenance acts on the equipment’s actual condition and data, rather than a fixed calendar. This guide is about starting that data-driven approach from the data you already have.
How is 90 days realistic with no model training?: The first value comes from making existing signal queryable and traceable, not from training a model on labelled data. You connect a source, baseline it, surface patterns, and act — measured against day one.
What do we actually need to connect first?: One critical line or asset family: its CMMS history and the relevant SCADA alarms, read-only. Add ERP/MES context where root cause requires it.

Map your first 90 days.

Bring one critical line — we’ll show what your existing CMMS and SCADA data already reveal about it.

Book a demo